Mass movement characterization using a reflexion and refraction seismic survey with the sloping local base level concept

This study proposes a new concept for upscaling local information on failure surfaces derived from geophysical data, in order to develop the spatial information and quickly estimate the magnitude and intensity of a landslide. A new vision of seismic interpretation on landslides is also demonstrated by taking into account basic geomorphic information with a numeric method based on the Sloping Local Base Level (SLBL). The SLBL is a generalization of the base level defined in geomorphology applied to landslides, and allows the calculation of the potential geometry of the landslide failure surface. This approach was applied to a large scale landslide formed mainly in gypsum and situated in a former glacial valley along the Rhône within the Western European Alps. Previous studies identified the existence of two sliding surfaces that may continue below the level of the valley. In this study, seismic refraction–reflexion surveys were carried out to verify the existence of these failure surfaces. The analysis of the seismic data provides a four-layer model where three velocity layers (< 1000 m s− 1, 1500 m s− 1 and 3000 m s− 1) are interpreted as the mobilized mass at different weathering levels and compaction. The highest velocity layer (> 4000 m s− 1) with a maximum depth of ~ 58 m is interpreted as the stable anhydrite bedrock. Two failure surfaces were interpreted from the seismic surveys: an upper failure and a much deeper one (respectively 25 and 50 m deep). The upper failure surface depth deduced from geophysics is slightly different from the results obtained using the SLBL, and the deeper failure surface depth calculated with the SLBL method is underestimated in comparison with the geophysical interpretations. Optimal results were therefore obtained by including the seismic data in the SLBL calculations according to the geomorphic limits of the landslide (maximal volume of mobilized mass = 7.5 × 106 m3).